Short timescale rate maximization by gulls and implications for predation on size-structured prey
Bibliographic record
Abstract
The timescale over which a predator estimates changes in prey encounter rates will play an important role in maximization of energetic returns from foraging in habitats where prey availability is highly variable through time. However, studies that explicitly test the temporal scale over which foragers track changes in prey availability are surprisingly rare. The increasingly well-recognized impact of terrestrial predators (e.g., birds) on intertidal food webs is likely to depend on their ability to track prey fluctuations in these highly variable environments. Here, we compare the predictions of 2 optimal diet models: a “classic” model in which prey encounter rate estimates are based on long-term, site-level abundance averages, and a model in which encounter rate estimates change at regular intervals throughout the foraging period. We parameterized these models using data from a field study on glaucous-winged gulls ( Larus glaucescens ) foraging on various sizes of the sea star Pisaster ochraceus . Predictions from the classic model, which assumes constant diet breadth throughout the tide cycle, did not match field observations of diet breadth. The “tide-sensitive” model, which assumes that gulls track tide-related changes in prey abundance, provided a better fit to observational data, explaining the full range of Pisaster sizes consumed by gulls. We conclude that gulls track short-term changes in prey encounter rates within a single low tide period to maximize foraging returns. We also present data for high rates of Pisaster removal by gulls, challenging the view of this sea star as a top predator in its intertidal communities.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".